Research and Data Analysis

SAS Programming for Advanced Statistical Procedures Training Course

Introduction

In today’s data-driven research environment, the ability to manage, analyze, and report on sensitive topics such as mental health, gender identity, substance abuse, and social inequalities requires not only technical expertise but also ethical sensitivity and methodological rigor. SAS Programming for Advanced Statistical Procedures Training Course equips researchers, data scientists, and analysts with in-demand SAS programming skills, allowing them to design and implement statistically valid procedures for sensitive research domains.

Participants will gain hands-on experience in using SAS for complex data structures, applying advanced statistical models, and implementing data privacy techniques. With real-world case studies and a problem-solving approach, this course ensures learners are well-prepared to tackle high-impact research challenges using cutting-edge analytical tools while maintaining ethical research standards.

Programme Curriculum

SAS Programming for Advanced Statistical Procedures Training Course

Introduction

Course Objectives

Understand ethical considerations in researching sensitive data.
Apply advanced SAS programming for data manipulation and modeling.
Perform multivariate analysis on sensitive datasets.
Use data anonymization and masking techniques.
Implement logistic and ordinal regression models in SAS.
Conduct survival analysis on longitudinal sensitive data.
Integrate machine learning procedures in SAS for predictive modeling.
Handle missing data using multiple imputation techniques.
Develop macro programs to automate complex analyses.
Visualize confidential insights using secure SAS reporting tools.
Conduct sensitivity analysis and validate models effectively.
Work with multi-source sensitive datasets using data merging strategies.
Document and interpret outputs with reproducible research techniques.

Target Audiences

Academic Researchers
Government Data Analysts
Health and Social Science Professionals
NGO Research Officers
Clinical Trials Statisticians
Graduate Students in Data Science
SAS Programmers
Public Policy Analysts

Course Duration: 10 days

Course Modules

Module 1: Introduction to Sensitive Topics in Research

Overview of sensitive research domains
Ethical concerns in human-subject research
IRB compliance and approval workflows
Cultural competency in survey/questionnaire design
Risk assessment and mitigation
Case Study: Researching adolescent mental health data

Module 2: SAS Fundamentals for Sensitive Data

Data step vs proc step: Practical insights
Importing/exporting secure data
SAS libraries and metadata management
SAS log interpretation and error handling
Formats/informats for privacy-compliant datasets
Case Study: Gender-based violence survey data

Module 3: Advanced Data Cleaning and Management

Detecting and managing outliers
Standardizing data from multiple sources
Creating derived variables securely
Restructuring longitudinal data
Ensuring traceability in transformation steps
Case Study: Cleaning datasets from anonymous online forums

Module 4: Data Anonymization and Privacy Techniques

De-identification vs pseudonymization
Hashing and scrambling identifiers in SAS
Data masking functions and macros
Secure merging and linking of datasets
Legal and ethical obligations in data protection
Case Study: Handling patient data in a trauma registry

Module 5: Descriptive Statistics with Ethical Emphasis

Summary statistics for sensitive variables
Frequency analysis for categorical data
Cross-tabulations in secure environments
Avoiding re-identification in small cell sizes
Reporting techniques for sensitive indicators
Case Study: Reporting suicidal ideation in teen populations

Module 6: Regression Models for Categorical Data

Binary logistic regression
Multinomial and ordinal logistic regression
Model diagnostics and fit measures
Interpreting coefficients in sensitive contexts
Dealing with quasi-complete separation
Case Study: Analyzing intimate partner violence survey data

Module 7: Survival Analysis in Sensitive Research

Kaplan-Meier curves in censored data
Cox proportional hazards modeling
Time-varying covariates and risk factors
Stratified analysis for demographic groups
Visualizing survival trends ethically
Case Study: Tracking recovery time for PTSD patients

Module 8: Handling Missing Data Ethically

Mechanisms: MCAR, MAR, MNAR
Patterns of missingness in sensitive variables
Multiple imputation using PROC MI
Imputation diagnostics and sensitivity analysis
Reporting post-imputation results
Case Study: Missing responses in drug abuse research

Module 9: Multivariate Analysis Using SAS

Factor analysis for psychosocial metrics
Principal component analysis (PCA)
Cluster analysis with ethical safeguards
Canonical correlation in social science datasets
Interpretation of high-dimensional output
Case Study: Mental health burden index among refugees

Module 10: Macro Programming in SAS

Writing reusable macro programs
Parameterization for flexibility
Conditional logic in macros
Automating analysis workflows
Debugging and validation
Case Study: Automating analysis of sensitive income data

Module 11: Machine Learning Techniques in SAS

Decision trees and random forests
Neural networks for classification
Model training/testing with sensitive inputs
Overfitting and ethical overreach
SAS Viya integration for ML
Case Study: Predicting domestic violence risk

Module 12: Visual Analytics and Secure Reporting

Creating secure dashboards in SAS
Data redaction for visualization
Annotated graphs with ethical framing
Interactive reports for non-technical users
Infographics and stakeholder reporting
Case Study: Visualizing elder abuse trends

Module 13: Data Integration and Linking Strategies

Merging datasets with sensitive keys
Master/slave data structures
Fuzzy matching for anonymized records
Quality checks in merge processes
Avoiding linkage bias
Case Study: Linking hospital and police records

Module 14: Sensitivity Analysis and Model Validation

Bootstrap and jackknife techniques
Assessing robustness of findings
Stress-testing assumptions
Cross-validation in high-risk datasets
Documentation of sensitivity procedures
Case Study: Substance use predictors in minority groups

Module 15: Reproducible Research and Documentation

Version control using Git with SAS
Writing SAS logs for auditing
Output Delivery System (ODS) best practices
Annotated code documentation
Ethical archiving and publication readiness
Case Study: Publishing sensitive results in peer-reviewed journals

Training Methodology

Instructor-led hands-on labs using real anonymized datasets
Case-based learning to simulate sensitive real-world scenarios
Use of guided SAS coding exercises with peer review
Ethical debates and breakout discussions
Take-home projects with feedback on statistical and ethical integrity
Access to recorded lectures and secured sample codes

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

SAS programming advanced statistics data analysis

Programme Fee

Duration: 10 Days

Method: Online or Physical

Online Price: $2,000

Physical Price: $3,000

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 30 Oct 2026

💻 Online / Virtual session

Online $2,000